We propose a unified framework for Ensemble Block Co-clustering (EBCO) which aims to fuse multiple basic co-clusterings into a consensus structured affinity matrix. Each basic coclustering is obtained with a co-clustering method on the same document-term dataset. This fusion process reinforces the individual quality of the multiple basic data co-clusterings within a single consensus matrix. The proposed framework enables an unsupervised co-clustering where the number of co-clusters is inferred based on the non trivial generalized modularity. We define an explicit objective function which allows the joint learning of the basic co-clusterings aggregation and the consensus block co-clustering (Affeldt et al., 2020).