```json
{
    "no": ["tertiary", "secondary", "unknown", "primary"],
    "yes": ["tertiary", "secondary", "unknown"]
}
```
In this dataset, the feature "education level" consists of categorical variables with the categories ['tertiary', 'secondary', 'unknown', 'primary']. 

Based on the analysis of the relationship between the feature and the task, the values of education level for "no" and "yes" classes observe the following:

For clients who do not subscribe to a term deposit ("no" class), the possible values of education level are ['tertiary', 'secondary', 'unknown', 'primary'].

For clients who subscribe to a term deposit ("yes" class), the possible values of education level are ['tertiary', 'secondary', 'unknown'].

Please note that the values present in the dictionary may not account for all possible values of the feature education, especially if there are hard-to-predict education levels not observed in the data.