Abstractive summarization is a technique in natural language processing that generates a concise summary of a text by creating new sentences rather than just extracting key phrases. This method aims to capture the main ideas and themes of the original content while rephrasing it in a more coherent and readable form. Unlike extractive summarization, which pulls direct quotes from the text, abstractive summarization involves understanding the context and meaning behind the words. It is often used in applications like news articles, research papers, and customer reviews to provide quick insights without losing essential information.