Learning and reasoning are both essential abilities associated with intelligence and machine learning and machine reasoning have received considerable attention given the short history of computer science. The statistical nature of machine learning is now understood but the ideas behind machine reasoning is much more elusive. Converting ordinary data into a set of logical rules proves to be very challenging: searching the discrete space of symbolic formulas leads to combinatorial explosion (cite). Algorithms for probabilistic inference (cite) still suffer from unfavourable computational properties (cite). Algorithms for inference do exist but they do however, come at a price of reduced expressive capabilities in logical inference and probabilistic inference.
Humans display neither of these limitations.