The problem is you are not tuning your model. You need to find good values for $C$ and $\gamma$. In your case, the defaults turn out to be bad, which leads to trivial models that always yield a certain class. This is particularly common if one class has much more instances than the others. What is your class distribution?

scikit-learn has limited hyperparameter search facilities, but you can use it together with a tuning library like Optunity. An example about tuning scikit-learn SVC with Optunity is available here.

_{Disclaimer: I am the lead developer of Optunity.}

A likely cause is the fact you are not tuning your model. You need to find good values for $C$ and $\gamma$. In your case, the defaults turn out to be bad, which leads to trivial models that always yield a certain class. This is particularly common if one class has much more instances than the others. What is your class distribution?

scikit-learn has limited hyperparameter search facilities, but you can use it together with a tuning library like Optunity. An example about tuning scikit-learn SVC with Optunity is available here.

_{Disclaimer: I am the lead developer of Optunity.}