Understanding the mechanisms of statistical learning, where organisms infer structure from sensory observations without explicit instruction, is crucial in comprehending how the brain processes and responds to complex environments. This work explores the innate capabilities of both humans and mice to discern environmental regularities, focusing on the role of the hippocampus in this implicit learning processes. We use pupillometry to measure whether animals can detect and track patterns in rapidly unfolding sounds. The study leverages a novel comparative behavioural paradigm, termed X-detection, to manipulate the statistics of embedded tone sequences (patterns) in an auditory cover task: subjects should respond to a target sound, X, that appears at a random time. We show pupil responses in mice and humans track statistics of presented patterns, with limited exposure. Importantly, these embedded patterns are decoupled from the X; therefore, from the reward. We show that the performance on X-detection is not affected by the patterns. This paradigm allows probing of implicit learning of sound statistics without reinforcing the learning via reward. Our inactivation results, from bilateral infusion of dCA1 with GABA-A agonist muscimol, shows hippocampal inactivation, despite sparing the performance on X-detection, diminishes the pupil response tracking the statistics. To our knowledge, these results provide the first set of evidence, in rodents, for causal role of hippocampus in fast statistical learning of sound statistics.