Machine Learning Models are algorithms that enable computers to learn from data and make predictions or decisions without being explicitly programmed. They analyze patterns in large datasets to improve their performance over time. Common types of models include linear regression, decision trees, and neural networks, each suited for different types of tasks. These models are trained using historical data, allowing them to recognize trends and relationships. Once trained, they can be applied to new data to generate insights or automate processes. The effectiveness of a model often depends on the quality and quantity of the data used during training.