Extractive Summarization is a technique in natural language processing that involves selecting key sentences or phrases from a text to create a concise summary. This method focuses on identifying the most important parts of the original content without altering the wording, making it easier for readers to grasp the main ideas quickly. The process typically uses algorithms to analyze the text and determine which sentences carry the most weight based on factors like frequency of important words and sentence position. Machine Learning and NLP tools are often employed to enhance the accuracy and relevance of the extracted summaries.