The term 'machine learning model' in data science implies a mathematical framework that enables computers to learn from data and make predictions or decisions based on that data. These models are trained on large datasets, identifying patterns and relationships within the data. Machine learning models can be classified into various types, such as supervised, unsupervised, and reinforcement learning, each serving different purposes. In practice, these models are applied in diverse fields, including finance, healthcare, and marketing, facilitating data-driven decision-making and automation of complex tasks.