In active learning, a learner can make membership queries to the target concept c, asking for its value c(x) on inputs x chosen by the learner.
This passive learning type is also the most common scheme in supervised learning: a learning algorithm typically takes the training examples fixed, without the ability to query the label of unlabelled examples.