Collaborative filtering is a technique used in recommendation systems to suggest items based on user preferences. It analyzes patterns from multiple users to identify similarities in their choices. For example, if User A and User B both liked Movie X, and User A also liked Movie Y, the system might recommend Movie Y to User B. This method relies on the idea that users who agreed in the past will likely agree in the future. Collaborative filtering can be applied to various domains, including movies, music, and products, making it a popular choice for platforms like Netflix and Amazon.