Based on the given feature "education level" and the task of predicting whether a client subscribes to a term deposit or not, we can analyze the relationship between the feature and the target variable.

Here is the analysis:

- For the target class "no," the possible values of the feature "education level" could be ['tertiary', 'secondary', 'unknown', 'primary']. Clients with different education levels may choose not to subscribe to a term deposit.
- For the target class "yes," the possible values of the feature "education level" could also be ['tertiary', 'secondary', 'unknown', 'primary']. However, it is possible that clients with certain education levels are more likely to subscribe to a term deposit compared to others.

Based on this analysis, we can create the dictionary as follows:

```json
{
	"no": ["tertiary", "secondary", "unknown", "primary"],
	"yes": ["tertiary", "secondary", "unknown", "primary"]
}
```

Note: The list of education levels for each target class includes all the available categories.