Keyword extraction in the context of a Learning Management System (LMS) involves identifying and extracting important keywords or phrases from educational content, discussions, assignments, or other text-based resources within the system. This is beneficial for content organization, search optimization, and improving the overall usability of the LMS. Keyword extraction plays a pivotal role in Natural Language Processing (NLP), information retrieval, and text analysis. NLP algorithms can analyze the text, identify important terms, and extract keywords in reviews based on factors such as frequency, relevance, and context. This paper provides an overview of unsupervised keyword extraction algorithms like TextRank,  Yet Another Keyword Extractor (YAKE), and Latent Dirichlet Allocation (LDA)which are used to extract the keywords from student’s reviews and evaluation metrics precision, recall, and F1-score helps us to identify and evaluate the performance of keyword extraction algorithms.