In recommendation systems, machine learning models play a crucial role by analyzing user preferences and behaviors to suggest relevant content or products. These models leverage data from user interactions, such as clicks, ratings, and purchases, to identify patterns and predict what users may enjoy in the future. By employing algorithms like collaborative filtering or content-based filtering, recommendation systems enhance user experience, increase engagement, and drive sales in platforms such as e-commerce sites and streaming services.