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Morpho Challenge is an annual evaluation campaign for unsupervised morpheme analysis. In morpheme analysis, words are segmented into smaller meaningful units. This is an essential part in processing complex word forms in many large-scale natural language processing applications, such as speech recognition, information retrieval, and machine translation. The discovery of morphemes is particularly important for morphologically rich languages where inflection, derivation and composition can produce a huge amount of different word forms. Morpho Challenge aims at language-independent unsupervised learning algorithms that can discover useful morpheme-like units from raw text material. In this paper we define the challenge, review proposed algorithms, evaluations and results so far, and point out the questions that are still open.