A company is building a recommendation system to provide personalized product suggestions to its customers. The company has collected historical user interaction data - including product views, purchases, and ratings. An ML engineer needs to select the most suitable built-in Amazon SageMaker algorithm to train the recommendation model efficiently. The engineer wants a solution that minimizes development effort while providing high-quality recommendations. Which built-in SageMaker algorithm should the ML engineer use to meet these requirements?