The correct answer is C. Unsupervised learning.
In unsupervised learning, the algorithm learns from data without any labeled training data. The algorithm must identify the patterns and structure in the data on its own. This type of learning is often used for tasks such as clustering and dimensionality reduction.
Supervised learning is a type of machine learning in which the algorithm is trained on labeled data. The labels provide the algorithm with feedback on whether its predictions are correct or incorrect. This type of learning is often used for tasks such as classification and regression.
Reinforcement learning is a type of machine learning in which the algorithm learns from trial and error. The algorithm is given a goal and must learn how to achieve that goal by interacting with its environment. This type of learning is often used for tasks such as playing games and controlling robots.
In the given question, the learning is based on feedback provided by the environment, but there are no actual supervisors. This means that the learning is unsupervised.