With the huge volume of digital data, clustering algorithms are providing efficient tools for data organizing and analyzing. Clustering algorithms are used in various domains such as bioinformatics, speech recognition, and information retrieval. Clustering is an automatic technique that divides a set of data objects into smaller groups such that the objects within a group are similar to each other and dissimilar to objects in other groups as much as possible. This paper reviews and discusses different clustering algorithms, their concepts, advantages, and limitations. A comparison among clustering algorithms will also be represented based on certain criteria.