Recommending systems primarily rely on collaborative filtering algorithms. These algorithms analyze user behavior and preferences to recommend items based on similarities between users or items. Collaborative filtering can be user-based or item-based, allowing systems to generate personalized suggestions. This methodology is commonly used in platforms like Netflix and Amazon to enhance user experiences by delivering relevant content and products tailored to individual preferences, improving user engagement and satisfaction.