The paradigm of QML is a transformative and cutting- edge research domain that fuses the methodologies

from Machine Learning (ML), Quantum Computing (QC) together forming a novel framework for enhancing system throughput and problem solution finding potential intelligently. Belonging to the broader realm of Artificial Intelligence (AI) technologies, machine learning (ML) leverages advanced computing capabilities and diverse algorithm approaches to address the challenges for application spanning areas lik chemistry,agriculture,hospitals, drug manufacturing, NLP, etc. Notwithstanding heritage in the processing of classical data, quantum machine learning processes the classical data by using the machine learning algorithm to explore the quantum phenomenon in the learning system. Quantum machine learning is a ground breaking change to computer science that may exponentially speed up the processing, as well as work with large, and complex datasets. This study emphasizes the contrasting aspects of classical and quantum machine learning and concludes with a discussion on the potential pathways and existing challenges in achieving quantum advantage through the framework of QML.