Machine learning enables recommendation systems by analyzing user behaviors, preferences, and patterns to predict future actions. These systems utilize algorithms to process vast amounts of data, identifying relationships and trends that inform personalized suggestions. By employing techniques such as collaborative filtering and content-based filtering, they can recommend products, movies, or services tailored to individual users. This personalization enhances user experience, boosting engagement and conversion rates. As a result, recommendation systems play a crucial role in e-commerce, streaming services, and social media, driving both customer satisfaction and business revenue.