"Collaborative filtering" implies a technique used in recommendation systems that suggests products or content based on user behaviors and preferences. It analyzes the interactions among users and items within a dataset, identifying patterns that enable personalized recommendations. For instance, if User A and User B have similar tastes, the system can recommend items that User A enjoyed to User B. This data-driven approach enhances user experience by tailoring recommendations to individual preferences, thereby increasing engagement and satisfaction within platforms like e-commerce sites and streaming services.