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Introduction: Biosensors have emerged as critical analytical surfaces in the swift, delicate, and discerning identification of biological and chemical analytes in healthcare, environmental detection, food safety, and therapeutics. Nanotechnological progress has provided a big step in biosensor sensitivity, selectivity, and signal stability, and made it possible to miniaturise portable and real-time biosensing devices to be used in point-of-care devices and in wearable applications. Methods: The literature included in this review is systematically analyzed from peer-reviewed studies published from 2005 to 2025 that were found in the large scientific databases of PubMed, Scopus, Web of Science, IEEE Xplore, ScienceDirect, and Google Scholar. The articles were chosen by the criterion of relevance to biosensor design, biorecognition components, nanomaterials-based transduction systems, analytic performance, and biomedical or environmental uses. The evaluation of technological advancement and translational viability was done using qualitative synthesis and comparative analysis. Results: The literature examined demonstrates that biosensors, which use nanomaterials, with metal nanoparticles, carbon nanotubes, quantum dots, and nanowires, have lower detection limits and shorter response times and better reliability in their analysis than traditional platforms. Progress in the electrochemical and optical transductions and mass-based transduction techniques has paved the path towards label-free and multiplexed detection, which opens up the way for wearable and point-of-care biosensing systems. Discussion: Although there has been a major advancement, there are still challenges like variability of nanomaterials, biofouling, inability to achieve long-term stability, scalability, and constraints in regulations, to name a few. These problems can be resolved through improvements in surface engineering, protocol fabrication, antifouling mechanisms, and signal processing based on information. Conclusion: Nanostructured biosensors offer a good platform for the next-generation diagnostics and monitoring technology. Further interdisciplinary optimisation and translational validation will be necessary to achieve the success of clinical adoption and a large-scale implementation.