1. An information estimation system comprising: a preference model generating unit that generates a preference model by learning and storing the preference model for a user based on a behavior history that indicates history of behavior of the user, wherein the preference model is stored in a preference model database; an evaluation list generating unit that calculates probability of a plurality of recommended candidates based on the preference model and generates an evaluation list indicating the probability of the recommended candidates; a default predicting unit that specifies habituation of the user based on the information on the behavior history and calculates a predicted default value of the plurality of recommended candidates based on the habituation; and an evaluated unexpectedness value calculating unit that calculates an evaluated unexpectedness value indicating unexpectedness where the unexpectedness is higher as a difference is larger, the difference being obtained by subtracting the predicted default value from the probability, wherein the evaluated unexpectedness value calculating unit raises the priority of the recommended candidate when the recommended candidate having a relatively high evaluated unexpectedness value calculated by the evaluated unexpectedness value calculating unit is matched with the recommended candidate having the probability that is relatively high in the evaluation list prepared by the evaluation list generating unit.