Consensus clustering: how to choose the final cluster based on the consensus matrix?
Consensus clustering is an additional evaluation technique (i.e. how much consensus is there between clusters), like the Silhouette score, rather than explicit clustering.
The clusters themselves would drop out earlier in the processing. The consensus metric is used to test for the best K value, in the K-means clustering algorithm.