The correct answer is: A. given email labeled as spam or not spam, learn a spam filter.
Supervised learning is a type of machine learning in which the model is trained on labeled data. This means that the model is given a set of data that includes both the input data and the desired output. The model then learns to map the input data to the output data.
In the case of spam filtering, the input data would be the email messages, and the desired output would be whether the message is spam or not. The model would be trained on a set of email messages that have been labeled as spam or not spam. The model would then learn to identify the features that are associated with spam messages, and use those features to classify new email messages as spam or not spam.
The other options are not examples of supervised learning. In option B, the model is not given any labeled data. In option C, the model is given a database of customer data, but the data is not labeled. In option D, the model is given a set of data, but the data is not labeled.
Supervised learning is a powerful tool that can be used to solve a variety of problems. However, it is important to note that supervised learning requires labeled data. If labeled data is not available, then supervised learning cannot be used.