The exponential growth of data generated from various sources has ushered in the era of big data, which poses unique challenges in terms of volume, velocity, variety, and veracity. Traditional data processing techniques often fall short in effectively managing and extracting insights from this vast and complex data landscape. Machine learning (ML) has emerged as a transformative solution, offering powerful algorithms capable of analyzing large datasets to uncover meaningful patterns and drive informed decision-making. This paper provides a comprehensive review of key machine learning algorithms utilized in big data analytics, encompassing supervised, unsupervised, and deep learning approaches.