 Electrochemical biosensors are a class of biosensors that use biological recognition elements, such as biochemical receptors, to convert analyte concentrations into electrical signals. These sensors are used in a variety of fields including food safety, medical science, defense, and plant biology. They provide a reliable and cost-effective way to measure analyte concentrations in body fluids like sweat, blood, feces, and urine. Combinations of suitable immobilization techniques with effective transducers give rise to an efficient biosensor. However, the large amount of data generated from these sensors makes manual interpretation difficult. Machine learning algorithms help to remove signals obtained from contaminants and improve the overall sensitivity of the sensor. Additionally, electrochemical biosensors are susceptible to impurities, which can reduce their accuracy. Machine learning algorithms can be used to identify and eliminate these impurities, thus improving the accuracy of the sensor. Finally, this review discusses the various types of electrochemical biosensors, their applications, the importance of ML and biosensing, and challenges and future outlook. This article was authored by Anup Singh, Asha Sharma, Amir Ahmed, and others. We are article.tv, links in the description below.