The type of machine learning that requires no human intervention for pattern recognition is called unsupervised learning. In this approach, algorithms analyze data sets without labeled outputs, identifying inherent structures and patterns. This method is especially useful for tasks such as clustering, where similar data points are grouped without prior knowledge of categories.