The correct answer is a regression model, which is designed to predict a continuous value based on input parameters. Unlike classification models that categorize inputs (e.g., identifying if an image is a car or a truck), regression models are ideal for forecasting numerical outcomes, such as sales quantities. Features are attributes used within models to describe data instances, and reinforcement learning involves an agent learning from its environment through actions and rewards. For more details, visit Google Cloud's AutoML Tables documentation on problem types.