In the Feature Store, selecting specific features for model training involves using a function that retrieves the desired features from a feature table. The most suitable option is to use fs.feature_lookup() with specified features. This function is typically provided by the Feature Store API and allows you to specify the features you want to retrieve from a particular feature table, acting like a lookup mechanism based on feature names or identifiers. Other options either do not pertain to feature selection (fs.create_model(), fs.create_feature_table()) or are not as commonly used (fs.select_features()). Not specifying features when using fs.create_training_set() might result in the entire feature table being used, which is often not desirable. Therefore, fs.feature_lookup() is the targeted method for retrieving the specific features needed for training from the Feature Store.