Hybrid Recommender Systems combine multiple recommendation techniques to improve accuracy, overcome limitations of individual methods, and provide more robust recommendations. They leverage the strengths of collaborative filtering, content-based filtering, and other algorithms to deliver personalized user experiences across various domains.