In our education system, teacher hopes his students to learn something specific from his demonstrations and textbook, his students try to understand his teacher’s demonstration and textbook by their own learning methods. Obviously, the aim of the teacher may not be achievable for all students’ learning methods. Therefore, students’ final learning results are different from teacher’s expectation in gen-eral, which is called the gap between teaching and learning (in short, GTL) in this paper. As the goal of machine learning is to design a computer program with learning ability, it is naturally questioned if GTL occurs in the machine learning fields. In this paper, we prove that there exists GTL in machine learning. As a common assumption in the current learning theory is that a learning al-gorithm usually realizes the original expecta-tion, GTL provides a new insight into learn-ing theory. According to the GTL Theory, the learning algorithms can be classified into four types, Type I through Type-IV. Comparison with human learning, the GTL Theory sub-stantiates an intuitive observation: artificial intelligence can never surpass human intelli-gence from the learning point of view.