  Studies addressing the question "Can a learner complete the learning
securely?" have recently been spurred from the standpoints of fundamental
theory and potential applications. In the relevant context of this question, we
present a classical-quantum hybrid sampling protocol and define a security
condition that allows only legitimate learners to prepare a finite set of
samples that guarantees the success of the learning; the security condition
excludes intruders. We do this by combining our security concept with the bound
of the so-called probably approximately correct (PAC) learning. We show that
while the lower bound on the learning samples guarantees PAC learning, an upper
bound can be derived to rule out adversarial learners. Such a secure learning
condition is appealing, because it is defined only by the size of samples
required for the successful learning and is independent of the algorithm
employed. Notably, the security stems from the fundamental quantum
no-broadcasting principle. No such condition can thus occur in any classical
regime, where learning samples can be copied. Owing to the hybrid architecture,
our scheme also offers a practical advantage for implementation in noisy
intermediate-scale quantum devices.
