This talk examines Counterfactual Explaination (CE) as a mapping of the data manifold into itself. Through this lens, it aims (1) to expose and clarify the implicit assumptions underlying the procedural CE approaches, and (2) to set qualitative criteria such as "plausibility", "similarity", "validity", "sparsity" on a clearer formal basis. This simple exercise highlights several overlooked conceptual aspects of CE.