The cluster assumption is assumed in many machine learning algorithms such as the k-nearest neighbor classification algorithm and the k-means clustering algorithm. As the word "likely" appears in the definition, there is no clear border differentiating whether the assumption does hold or does not hold. In contrast the amount of adherence of data to this assumption can be quantitatively measured.
