In recent years, machine learning has always been a research hotspot, and has been applied to various fields with an important role played. However, as the data amount continues to increase, the training time of machine learning algorithms is getting longer. Meanwhile, quantum computers demonstrate a powerful computing ability. Therefore, researchers try to solve the problem of long machine learning training time, which leads to the emergence of quantum machine learning. Quantum machine learning algorithms have been proposed, including quantum principal component analysis, quantum support vector machine, and quantum deep learning. Additionally, experiments have proven that quantum machine learning algorithms have a significant acceleration effect, leading to a gradual upward trend in research on quantum machine learning. This study reviews research on quantum machine learning algorithms. First, the fundamental concepts of quantum computing are introduced. Then, five quantum machine learning algorithms are presented, including quantum supervised learning, quantum unsupervised learning, quantum semi-supervised learning, quantum reinforcement learning, and quantum deep learning. Next, related applications of quantum machine learning are demonstrated with the algorithm experiments provided. Finally, the relevant summary and prospect of future study are discussed.